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Leprosy (Hansen's disease) is an infectious, neglected tropical disease caused by the Mycobacterium Leprae (M. Leprae). Each year there are approximately 2,02,189 new cases are detected globally. In the year 2017 more than half million people were disabled due to leprosy and almost 50000 new cases are added every year world wide. In leprosy, lepra reactions are the major cause for nerve damage leading to disability. Early detection of lepra reactions through study of biomarkers have important role in prevention of subsequent disabilities. To our knowledge there seems to be very limited literature available on within-host modeling at cellular level involving the crucial biomarkers and the possible optimal drug regimen for leprosy disease and lepra reactions. Motivated by these observations, in this study, we have proposed and analyzed a three dimensional mathematical model to capture the dynamics of susceptible schwann cells, infected schwann cells and the bacterial load based on the pathogenesis of leprosy. We estimated the parameters from various clinical papers to make the model more practical. The sensitivity of couple of parameters was evaluated through PRCC method to find out the single most influential parameter and also combination of two most influential parameters was studied using SRCC method. The sensitivity of other remaining parameters was evaluated using Sobol's index. We then have framed and studied an optimal control problem considering the different medication involved in the Multi Drug Therapy (MDT) as control variables. We further studied this optimal control problem along with both MDT and steroid interventions. The finding from this novel and comprehensive study will help the clinicians and public health researchers involved in the process of elimination and eradication of leprosy.